Digital Twin-driven Smart Human-machine Collaboration: Theory, Enabling Technologies and Applications

With the evolution of human-cyber-physical systems (HCPS), the relationships between human and machine evolved through different phases: from human-machine coexistence and human-machine interaction to human-machine cooperation and human-machine collaboration. Meanwhile, emerging technologies (e.g., digital twin) empower the industry and society with increased features of automation and intelligence, enhance the capabilities of perception, analyzing, control, and decision making. Those developments provide human-machine collaboration the foundation for paradigm shifting toward human-centric smart manufacturing. In this work, the concept of digital twin-driven smart human-machine collaboration is proposed based on the HCPS theory. By analyzing the evolutions of human-machine relationship and related definitions on human-machine collaboration, the connotation of smart human-machine collaboration is elaborated. The framework of digital twin-driven smart human-machine collaboration is proposed to address the current challenges in human-machine collaboration, from perspectives of physical entities, digital models, connection and interaction, and smart decision for collaborative service. The enabling technologies for smart human-machine collaboration are discussed from the aspects of sensing and integration, computation and analysis, control and execution, e.g., wearable technology, flexible sensing, artificial intelligence, exoskeleton. Furthermore, typical applications of smart human-machine collaboration are presented, including production, architecture construction, healthcare, and ergonomics. It is expected this work can provide a reference for facilitating paradigm shift of human-machine collaboration and the sustainable development of human-machine collaboration. © 2022 Editorial Office of Chinese Journal of Mechanical Engineering. All rights reserved.